Class Imbalance is a common challenge in statistics and machine learning where the distribution of the target variable is skewed, resulting in several issues such as bias towards the majority class or over-fitting.
However, and since machine learning is application and experimentation driven, class imbalance should not be handled in a nomothetic manner.