Could you define the concepts of overfitting and underfitting in machine learning, and explain their relevance in model development?

Interview question asked to Machine Learning Engineers interviewing at Grubhub, Amazon, Headspace and others: Could you define the concepts of overfitting and underfitting in machine learning, and explain their relevance in model development?.