Everything in mathematical models have roots in Plato’s true reality of Realm of Forms. According to Plato the Forms are abstract, perfect, unchanging concepts or ideals that transcend time and space; they exist in the Realm of Forms. In simpleton terms “Realm of Forms” is pure abstract mathematics. The real world is just a “shadow” that we able to observe. “Allegory of the cave” is a vivid representation of that philosophical concept.
Statistical modelling follows “Realm of Forms” precisely. Statistical term “population” is an entire pool from which a statistical sample is drawn. That’s your “form”. The sample is just an observation of the “population” that we able to see.
“Population” is driven by some random distribution. That distribution may have some parameters. Frequentists statisticians assume that those parameters are static numbers, and the goal is to create a most precise “estimate” possible. Bayesians assume that those parameters are randomly distributed. Distribution of those parameters is called “prior”.
Bayesian vs frequentist approaches have their own merits. Bayesian seems like a bit more consistent, and might be extended to general logic. The choice between the two should be driven by purely practical applications. Purity of the approach is irrelevant. Remember mathematics is just a tool like any other.