PERF: DataFrame.merge with MultiIndex issues PerformanceWarning
### 

- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this issue exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.

- [ ] I have confirmed this issue exists on the master branch of pandas.


### Reproducible Example

```
>>> import pandas as pd
>>> left = pd.DataFrame.from_dict({('A', 'a'): [0]})
>>> right = pd.DataFrame.from_dict({('B', 'b'): [1]})
>>> left.merge(right, how='cross')
PerformanceWarning: dropping on a non-lexsorted multi-index without a level parameter may impact performance.
  obj = obj._drop_axis(labels, axis, level=level, errors=errors)
   A  B
   a  b
0  0  1
```

It is neither `left.columns` nor `right.columns` that has `_lexsort_depth == 0`. Some MultiIndex created during the merge is not sorted (and/or dropped without a level parameter). I don't know if this actually affects performance or is better described as a bug.

### Installed Versions

INSTALLED VERSIONS
------------------
commit           : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python           : 3.8.10.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.11.0-27-generic
Version          : #29~20.04.1-Ubuntu SMP Wed Aug 11 15:58:17 UTC 2021
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : en_US.UTF-8

pandas           : 1.3.4
numpy            : 1.21.4
pytz             : 2021.3
dateutil         : 2.8.2
pip              : 21.2.4
setuptools       : 57.4.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

### Prior Performance

_No response_