If $$\mathbb{P}(|X_n-X|> \epsilon_n \, \, \text{i.o.}) = 0, \tag{1}$$ then $X_n \to X$ almost surely. This follows simply from the fact that $(1)$ means that for almost every $\omega \in \Omega$ we can find $N \in \mathbb{N}$ such that $$\omega \notin \{|X_n-X|>\epsilon_n\} \quad \text{for all $n \geq N$,}$$ i.e. $$|X_n(\omega)-X(\omega)| \leq \epsilon_n \quad \text{for all $n \geq N$.}$$ As $\epsilon_n \to 0$ as $n \to \infty$ we get $\lim_{n \to \infty} |X_n(\omega)-X(\omega)|=0$.
The converse does in general not hold true, i.e. $X_n \to X$ almost surely does in general not imply $(1)$ for an arbitrary sequence $\epsilon_n \to 0$. Consider for instance $X_n := 2/n$ and $\epsilon_n = 1/n$, then $X_n \to X=0$ almost surely but $$\mathbb{P}(|X_n-X|> \epsilon_n \, \, \text{i.o.}) = 1.$$
However, if $X_n \to X$ a.s. then we can always find a sequence $\epsilon_n \to 0$ such that $(1)$ holds. Indeed: As $X_n \to X$ almost surely we have
$$\mathbb{P} \left( \sup_{n \geq N} |X_n-X| \geq \epsilon \right) \xrightarrow[]{N \to \infty} 0$$
for any $\epsilon>0$. Choosing $\epsilon = 1/k$ for fixed $k \in \mathbb{N}$ this means that there exists $N_k \in \mathbb{N}$ such that
$$\mathbb{P} \left( \sup_{n \geq N_k} |X_n-X| \geq \frac{1}{k} \right) \leq \frac{1}{k^2}.$$
Without loss of generality, we may assume that $ N_1 < N_2 < \ldots$. Applying the Borel-Cantelli lemma we find that
$$\mathbb{P} \left( \sup_{n \geq N_k} |X_n-X| \geq \frac{1}{k} \, \, \text{for infinitely many $k$} \right)=0.$$
If we define
$$\epsilon_n := \frac{1}{k} \qquad \text{for} \, \, N_k \leq n < N_{k+1}, k \in \mathbb{N}$$
then this shows
$$\mathbb{P}(|X_n-X| \geq \epsilon_n \, \, \text{i.o.})=0.$$