How does Naïve Bayes handle multi-class classification scenarios?

Naïve Bayes naturally supports multi-class classification by computing posterior probabilities for each class independently.

For each class Ck, Naïve Bayes computes P(Ck|X) using Bayes theorem and selects the maximum. Unlike many binary classifiers, NB does not require one-vs-rest decomposition. Each class has its own parameter estimates for likelihood and prior.