Polynomial regression is a type of statistical technique used to model the relationship between a dependent variable and one or more independent variables. Unlike simple linear regression, which fits a straight line to the data, polynomial regression uses a polynomial equation to capture more complex relationships. This allows for curves in the data, making it useful for datasets that exhibit non-linear patterns. In polynomial regression, the degree of the polynomial determines the curve's complexity. A first-degree polynomial is a straight line, while higher degrees can create more intricate shapes. This flexibility helps in accurately predicting outcomes based on the input variables, making it a valuable tool in fields like data science and economics.