In simple words: Weight means influence; bias shifts the calculation.
One small unit
A perceptron is a simple artificial neuron. It receives numbers, multiplies each by a weight, adds a bias, and produces a result. A weight controls how strongly one input affects that result.
Why bias matters
Bias is an extra adjustable number. It lets the model shift its decision boundary instead of always starting from zero. The numbers are learned from examples during training.
See the flow
inputs × weights→add bias→output
Simple example
For a loan score, repayment history may receive a larger weight than income. Favourite colour should not be a useful input. The bias moves the score threshold.
Remember: Weight means influence; bias shifts the calculation.