BUG: pandas.groupby([A, B]).sum(level='B') gives cython_agg_general() error
#### Code Sample, a copy-pastable example

```python
import pandas as pd

A = [1, 2, 3]
B = [5, 5, 5]
C = [3, 2, 1]

df = pd.DataFrame(data={'A': A, 'B': B, 'C': C})
print("Method 1:\n", df.groupby(['A', 'C']).agg({'C': 'sum'}))  # works
print("Method 2:\n", df.groupby(['A', 'C']).sum(level='C'))  # gives error
```

#### Problem description

Last time I ran my code I could use the keyword _level_ to do statistics over a particular multiindex. Now, I get an error. Using agg is a workaround, but I'll have to rewrite quite a lot of code then. I couldn't find anything about the level kwarg being deprecated. Current output:

> Traceback (most recent call last):
> 
>   File "C:\Users\kahy\OneDrive - Skogforsk\Documents\Projekt\Översikt virkesmätning\Code\bugtest.py", line 19, in <module>
>     print("Method 2:\n", df.groupby(['A', 'C']).sum(level='C'))  # gives error
> 
>   File "C:\Program Files\Miniconda3\envs\kari_env\lib\site-packages\pandas\core\groupby\groupby.py", line 1371, in f
>     return self._cython_agg_general(alias, alt=npfunc, **kwargs)
> 
> TypeError: _cython_agg_general() got an unexpected keyword argument 'level'
> #### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.8.2.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
machine          : AMD64
processor        : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : en
LOCALE           : Swedish_Sweden.1252

pandas           : 1.0.3
numpy            : 1.18.1
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 46.2.0.post20200511
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : 3.0.3
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.13.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.1.3
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : None
xlsxwriter       : None
numba            : None
None

</details>
