What is the intuition behind kernel PCA vs SVM kernel?

Both use kernels, but SVM is supervised while kernel PCA is unsupervised.

SVM uses kernels to maximize class separation, while kernel PCA uses kernels to find principal components in transformed space. Both rely on similarity functions but serve different goals.