How does Naïve Bayes relate to likelihood-free inference approximations?

Naïve Bayes avoids likelihood-free inference because it assumes explicit parametric distributions.

Likelihood-free inference methods like ABC approximate distributions when likelihood is intractable. Naïve Bayes instead assumes explicit parametric forms (Gaussian, multinomial), enabling direct computation of likelihoods. This makes NB computationally efficient but less flexible than likelihood-free approaches.