People always said that naive Bayes is a linear model. I am not able to understand why, so can anybody explain?
I don't see how Naive Bayes is a linear model. This gives one possible definition. In general, I would say a linear model would involve a linear combination of the parameters or of some transformation of the parameters.
Naive Bayes multiplies the probabilities from the different variables and they are also not really weighted in the standard sense. However, if you take the logarithm this will become addition, so it is possible that given some type of conditional probability distribution (CPD) you could get something that looks like a linear model. I don't think this is true for every CPD though (but I may be wrong).