A prior distribution in Bayesian statistics represents the initial beliefs about a parameter before observing any data, influencing the posterior distribution after data is taken into account. It allows for the incorporation of existing knowledge or subjective judgment into statistical analysis, making Bayesian methods flexible and adaptive to new information.