Your question is Bias-Variance in Model Selection. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You're comparing several supervised learning models and want to choose one that will generalize well to new data.
What is the bias-variance tradeoff, and how does it affect model selection?