Answer
The bias variance tradeoff describes the balance between two types of error in a model: bias, which comes from overly simple assumptions, and variance, which comes from being too sensitive to the training data.
Real-world example A simple straight line model predicting house prices may miss important patterns, high bias, while a very complex model may fit every small detail of the training houses and fail on new houses, high variance.