The principle of indifference is a rule for assigning
epistemic probabilities. Suppose that there are n > 1 mutually exclusive and
collectively exhaustive possibilities. The principle of indifference states
that if the n possibilities are indistinguishable except for their names, then
each possibility should be assigned a probability equal to 1/n.

In Bayesian probability, this is the simplest non-informative
prior. The principle of indifference is meaningless under the frequency
interpretation of probability, in which probabilities are relative frequencies
rather than degrees of belief in uncertain propositions, conditional upon a
state of information.