19th century statistics was Bayesian while the 20th century was Frequentist, at least from the point of view of most scientific practitioners. The Bayesian-Frequentist debate reflects two different attitudes to the process of doing modeling, both looks quite legitimate.
In simple terms Bayesian statisticians are individual researchers, or a research group, trying to use all information they have to make quickest possible progress. While Frequentist statisticians draw conclusions from sample data by the emphasis on the frequency or proportion of the data only. They do not have any prior knowledge about the data. Hence, in Bayesian we have some prior knowledge while in Frequentist we don’t. You can find a more intuitive example about the difference between the two in layman terms –here.