Naive Bayes is a group of classification algorithms based on Bayes’ theorem and an assumption of independence between features used in the classifier. Features are not always independent, this is when Naive Bayes comes in handy because these type of algorithms can be successfully applied for various data science use cases, such as spam filtering or sentiment analysis.