Monte Carlo Integration
In Monte Carlo integration, the samples $x_1, x_2, \ldots x_N$ are independent, identically-distributed random variables. This implies they all have the same expectation value. The derived quantities $f(x_i)/p(x_i)$ also all have the same expectation value. So the expectation of a sum of $N$ of these is the same as $N$ times the expectation of any one of them:
$$E\left[ \sum_{i=1}^N \frac{f(x_i)}{p(x_i)} \right] = N \cdot E\left[\frac{f(x_1)}{p(x_1)}\right]$$
(I picked $x_1$ arbitrarily.)

Then, the expectation value of a continuous random variable is found by integrating over its probability measure:
$$E\left[\frac{f(x_1)}{p(x_1)}\right] = \int_{\text{domain of }p(x)} \frac{f(x)}{p(x)} \, p(x) \, dx$$