machine learning bias & variance

In ml model, there is an actual value in the dependent variable and the machine predicts a value according to the data. So bias is the distance/gap/difference between the actual value and predicted value. High bias means the gap is very much and low bias means the distance or gap is less or can be no gap or distance. Low bias model makes fewer assumptions about the form of the target function. A high bias makes more assumptions and for this reason it's unable to capture the important features of the dataset.