Convolution and Pooling as Infinitely strong priors

I am currently reading about Convolutional Neural Networks in Deep Learning Book. I am stuck on section 9.4 titled "Convolution and Pooling as Infinitely String Priors".

Could someone please intuitively explain to me what prior probability distribution is and what is its association to Convolution and Pooling operations in context of CNNs. Thank you!