Conjugate priors are a powerful tool in Bayesian statistics that simplify the process of updating beliefs with new data by ensuring that the posterior distribution is in the same family as the prior distribution. This property makes analytical solutions more tractable, allowing for easier computation and interpretation of Bayesian models.