Hi,
A couple of days ago I talked about something very similar here: What is effect of use_bias - #3 by lgusm
The Dense layers computes:
output = activation(dot(input, kernel) + bias)
A dense layer is trying to calculate: y= Ax + b
input (the x in the equation) are the data used for training
Kernel (the A in the equation) are the weights your layer is trying to find
Bias (b in the equation) is a vector.  The use_bias parameter configures the layer to calculate a bias vector together with with the weights. The initializer, regularizer and constraint will be used with the bias calculation is enabled.
for more information: tf.keras.layers.Dense  |  TensorFlow Core v2.5.0