REF: avoid unnecessary argument to groupby numba funcs
- [ ] closes #xxxx
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry

cc @mroeschke im pretty sure this is slightly more correct than the status quo, but i could use some help in coming up with test cases.  Two main cases to cover:

1) `res = df.groupby(more_than_one_column).transform(..., engine="numba", i_dont_know_off_the_top_the_calling_convention)`

I'm pretty sure in this case `res.index.names` will be wrong in master.

2) Cases with BinGrouper where there is a length mismatch (also an issue with non-numba paths)

```
import pandas as pd

df = pd.DataFrame(
        {
            "Buyer": "Carl Carl Carl Carl Joe Carl".split(),
            "Quantity": [18, 3, 5, 1, 9, 3],
            "Date": [
                pd.Timestamp(2013, 9, 1, 13, 0),
                pd.Timestamp(2013, 9, 1, 13, 5),
                pd.Timestamp(2013, 10, 1, 20, 0),
                pd.Timestamp(2013, 10, 3, 10, 0),
                pd.NaT,
                pd.Timestamp(2013, 9, 2, 14, 0),
            ],
        }
    )


gb = df.groupby(pd.Grouper(key="Date", freq="5D"))

gb.transform(lambda x: x, engine="numba", ...)  # <- pretty sure this raises
```

Or are these not reachable for some reason?