Parametric tests are statistical tests that make assumptions about the distribution of the data. For example, a t-test assumes that the data is normally distributed. Non-parametric tests do not make assumptions about the distribution of the data. Parametric tests are generally more powerful than non-parametric tests, but they are only valid if the data meets the Statistical Assumptions of the test.
Non-parametric tests are less powerful than parametric tests, but they can be used on any type of data, regardless of the distribution.