A conjugate prior is a prior distribution that, when combined with a likelihood function from the same family, results in a posterior distribution of the same family, simplifying Bayesian inference. This property makes it computationally convenient to update beliefs with new data, as the mathematical form of the distribution remains consistent throughout the analysis.