The relationship between likelihoood function and probability

Likelihood function. $\mathcal{L}(\theta | x) = p(x | \theta)$

This example from Wiki explains well

We have a coin, $\theta$ means probability of face of the thrown coin to be head.

(1) $\begin{equation*}\begin{cases}P_H = \theta \\P_T = 1-\theta\end{cases}\end{equation*}$

So, $P(HH | \theta=0.3) = 0.09$ means the the probability of two coin flips to be two heads when $\theta=0.3$ is 0.09.

Thus, $L(\theta=0.3 | HH) = 0.09$ means the likelihood of $\theta$ be 0.3 when we got two heads from two coin flips is 0.09.

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