BUG: MultiIndex drop produces wrong output if not lexicographically sorted
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.
  Latest Pandas version my system installs (via `anaconda update pandas`), which is 0.25.3.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---


#### Code Sample, a copy-pastable example

```python
import pandas as pd

df1 = pd.DataFrame(
    [
        [4, 5, 6],
        [5, 4, 6],
        [4, 5, 6],
        [3, 7, 5],
        [5, 9, 0],
        [1, 2, 3],
    ],
    columns=["a", "b", "c"],
)

df2 = pd.DataFrame(
    [
        [1, 2, 3],
        [4, 5, 6],
        [1, 6, 0],
    ],
    columns=["a", "b", "c"],
)

df1mi = pd.MultiIndex.from_frame(df1)
df2mi = pd.MultiIndex.from_frame(df2)
ismi = df1mi.intersection(df2mi)  # intersection of df1 and df2
# df1mi, _ = df1mi.sortlevel(sort_remaining=True)
complement = df1mi.drop(ismi).to_frame().reset_index(drop=True)

print(df1, "\n")
print(df2, "\n")
print(complement)
```

#### Problem description

Above code computes the multi-set complement A-B for two multi-sets A and B (only difference to sets is that duplicates in A that are not in B are preserved).

Without the commented-out line, pandas issues a warning (`sys:1: PerformanceWarning: indexing past lexsort depth may impact performance.`). However, the result is wrong: Row 1 from df1 is missing in the complement.

With the commented-out line, no warning is issued and the result is correct.

The bug is that without the sorting, the drop command malfunctions. 

#### Expected Output

Correct output (with explicit sort):

```
   a  b  c
0  3  7  5
1  5  4  6
2  5  9  0
```

Wrong output (without explicit sort):

```
   a  b  c
0  3  7  5
1  5  9  0
```

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.7.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 18.7.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : en_US.UTF-8
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 0.25.3
numpy            : 1.18.2
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 46.1.3.post20200330
Cython           : None
pytest           : 5.4.1
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.1
IPython          : 7.13.0
pandas_datareader: None
bs4              : 4.8.2
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.2.1
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : None
tables           : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None

</details>
