Not true. In frequentist statistics, from the perspective of Bayesians and non-Bayesians alike, there are no priors.

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Dear ChatGPT, are there priors in frequentist statistics? (Please answer with a single sentence.)

No — unlike Bayesian statistics, frequentist statistics do not use priors, as they treat parameters as fixed and rely solely on the likelihood derived from the observed data.

There's always priors, they're just "flat", uniform priors (for maximum likelihood methods). But what "flat" means is determined by the parameterization you pick for your model. which is more or less arbitrary. Bayesians would call this an uninformative prior. And you can most likely account for stronger, more informative priors within frequentist statistics by resorting to so-called "robust" methods.