The term Naive Bayes denotes that there is an naive assumption such that every feature is independent of other features and Bayes refers as a name of statistician Thomas Bayes.
Naive Bayes is one of the most simple algorithms for the classification and for large datasets.
The Bayes equation is
P(A|B) = Probability of A is true given that B is true.
P(B|A) = Probability of B is true given that A is true.
P(A)= Probability of A to be true.
P(B)= Probability of B to be true.
There are four terms in this equation,
Posterior, Likelihood, Prior, Marginal/Evidence