Homoscedasticity occurs when the error terms (difference between predicted and observed values) have equal or constant variance. This is a desirable characteristic and an assumption we want to make about regression models in particular in order to ensure that our error does not increase/decrease in relationship to one or more independent variables but remains consistent for the entire model.