The Naïve Bayes is a probabilistic classifier based on Bayes' theorem. This assumes strong (naive) independence assumptions between the features.
As long as features are not correlated and not repetitive, both Naïve Bayes and logistic regression will perform in a similar manner. However, when features are correlated and repetitive, the Naïve Bayes algorithm behaves differently due to its conditional independence assumption.
This is the mathematical equation for the Bayes theorem:
Here, A and B are events: