A Dense Layer will try to find the weights such as
y= Wx + b
W are the weights and b is the bias. When x is a matrix of values, W is also a matrix and b is a vector.
The use_bias parameter  tells the layer if you want to add (and calculate) this vector on your results.
My understanding of the bias is that enables the model to find weights to a function closer to the ground truth.
How it affects your results depends on the data complexity.
To have an even better understanding, I’d suggest you take a look on this colab: https://bit.ly/tf_basic_01 7