Quoting from a post on vampires, “In Bayesian inference, you start with some initial beliefs (called ‘Bayesian priors’ or just ‘priors’), and then you ‘update’ them as you receive new evidence.”
This is the standard metaphor, and it’s not so much wrong as unhelpful, misleading, and restricting. The metaphor derives from Bayes’s rule (details which can be looked up anywhere) and which gives a formula which on the right-hand-side is supposed to be an element representing “prior beliefs.” The formula itself is correct, as most math is. But because math is correct does not mean that it means what you think it means.
(Incidentally, all (as in all) frequentist methods should be dumped forthwith: no hypothesis testing, no p-values, no parameters, no infinities. It is a false dichotomy to suppose that if not Bayes then frequentist, and vice versa.)