how to handle values that only appear once in a column? Counting the values of a column using pandas I got the following result:

Human                 195
Mutant                 62
God / Eternal          14
Cyborg                 11
Human / Radiation      11
Android                 9
Symbiote                8
Kryptonian              7
Alien                   7
Demon                   6
Atlantean               5
Alpha                   5
Asgardian               5
Cosmic Entity           4
Inhuman                 4
Human / Altered         3
New God                 3
Animal                  3
Saiyan                  2
Eternal                 2
Frost Giant             2
Human-Kree              2
Demi-God                2
Human / Cosmic          2
Vampire                 2
Metahuman               2
Amazon                  2
Icthyo Sapien           1
Czarnian                1
Rodian                  1
Martian                 1
Clone                   1
Zombie                  1
Maiar                   1
Yoda's species          1
Human-Vulcan            1
Zen-Whoberian           1
Mutant / Clone          1
Korugaran               1
Dathomirian Zabrak      1
Parademon               1
Kaiju                   1
Flora Colossus          1
Human-Spartoi           1
Yautja                  1
Ungaran                 1
Human-Vuldarian         1
Neyaphem                1
Xenomorph XX121         1
Bizarro                 1
Human / Clone           1
Gungan                  1
Bolovaxian              1
Talokite                1
Luphomoid               1
Tamaranean              1
Kakarantharaian         1
Spartoi                 1
Strontian               1
Gorilla                 1
Name: Race, dtype: int64


I am new to data science, but I think that all those value appearing only once in the dataset is not going to help the classifier, so is there a good way to handle those values? I was thinking about grouping all those values that appear less than 5 times, or maybe I should remove the lines. By the way, I do not know if it is important to know, but I want to apply the gaussian naive bayes, knn and logistic regression to this dataset. This column is a feature to predict a binary value.
Assuming those are target categories, the most common strategies are:


Drop them. Do not try to predict categories with single observations because the model will overfit.
Bundle them to together into a "dustbin" category. Then the model can learn to predict "dustbin" category membership.