How Naïve Bayes Theorem is termed or named as Naïve?

A naive Bayes classifier assumes that the presence or absence of a particular feature of a class is unrelated to the presence or absence of any other feature, given the class variable. Fundamentally, it’s “naive” because it makes assumptions that may or may not turn out to be correct.

In other words, Naive Bayes (NB) is ‘naive’ because it makes the assumption that features of a measurement are independent of each other. This is naive because it is (almost) never true.