Why doesn't Postgres apply limit on groups when retrieving N results per group?

I've come across many questions/answers for Greatest/Top N per group type problems that explain _how_ to solve the problem - generally some variation of row_number() or CROSS JOIN LATERAL, but I'm struggling to understand the theory behind the _why_ for this example. The particular example I'm working with is this:

SELECT "orders".* 
FROM "orders" 
WHERE user_id IN (?, ?, ?, ?, ?)
ORDER BY "orders"."created_at" LIMIT 50

Essentially, I want to find the 50 most recent orders amongst a group users. Each user may have thousands of orders. I have two indexes - (user_id) and (user_id, created_at). Only the first index is ever used with this query. I can understand that the query planner would not know ahead of time which users would have those 50 newest orders. I imagined that it would be clever enough to determine that only 50 results are needed, and that it could use the (user_id, created_at) index to get 50 orders for each user. Then sort and filter those few hundred results in memory. Instead what I'm seeing is that it gets all orders for each user using the user_id index and then sorts/filters them all in memory. Here is an example query plan:

Limit  (cost=45271.94..45272.06 rows=50 width=57) (actual time=13.221..13.234 rows=50 loops=1)
  Buffers: shared hit=12321
  ->  Sort  (cost=45271.94..45302.75 rows=12326 width=57) (actual time=13.220..13.226 rows=50 loops=1)
          Sort Key: orders.created_at
          Sort Method: top-N heapsort Memory: 36kB
        Buffers: shared hit=12321
        ->  Bitmap Heap Scan on orders orders  (cost=180.85..44862.48 rows=12326 width=57) (actual time=3.268..11.485 rows=12300 loops=1)
                Recheck Cond: (orders.user_id = ANY ('{11,1000,3000}'::bigint[]))
                Heap Blocks: exact=12300
              Buffers: shared hit=12321
              ->  Bitmap Index Scan on index_orders_on_user_id  (cost=0.00..177.77 rows=12326 width=0) (actual time=1.257..1.258 rows=12300 loops=1)
                      Index Cond: (orders.user_id = ANY ('{11,1000,3000}'::bigint[]))
                    Buffers: shared hit=21
Planning:
  Buffers: shared hit=6
Execution time: 13.263 ms

The table I'm querying has roughly 50,000,000 orders, with an even distribution of ~4000 orders per user. I have found that I can speed this up significantly using CROSS JOIN LATERAL and it will use the composite index, but I'm struggling to understand WHY the CROSS JOIN LATERAL is needed here for it to use the index. So my question is, why doesn't Postgres use the composite index, and then retrieve only the minimum necessary amount of rows (50 per user) using the query I posted above? EDIT: More context This is the lateral join query that _does_ use the index

SELECT o.*
FROM company_users cu
CROSS JOIN LATERAL (
   SELECT *
   FROM orders o
   WHERE o.user_id = company_users.user_id
   ORDER  BY created_at DESC LIMIT 50
   ) cu
WHERE  cu.company_id = ? 
ORDER BY created_at DESC LIMIT 50

Doing a nested select like this doesn't use the index - even though it does a nested loop just like the lateral join does:

SELECT "orders".* 
FROM "orders" 
WHERE user_id IN (SELECT user_id FROM company_users WHERE company_id = ?)
ORDER BY "orders"."created_at" LIMIT 50